Vacancy search & MVP AI Agent
Budget: €750 – €1,500 EUR
I’m building an automated Agent that can read a candidate’s CV, LinkedIn profile, and the transcripts or summaries produced by Metaview, then instantly surface the most relevant open roles for them from across company career pages and job boards.
Here is what I need the agent to handle end-to-end:
• Ingest the three data sources (CV, LinkedIn profile, Metaview interview notes) and keep them linked to the same candidate record.
• Extract and normalise skills & competencies, work experience, plus any stated or implied preferences for the ideal next role. The skills and experience must be pulled from every data source, not just one.
• Use the consolidated profile to query company career pages, job boards or an internal vacancy API, rank matches by fit, and output a concise shortlist with an explanation of why each role is a match.
• Exclude vacancies from recruitment agencies, executive search and headhunting companies
• identify vacancy contact / hiring manager where possible
• Automate production of MVP email to the vacancy contact / hiring manager, with anonymised details of candidates. Where unable to automate the send, automate the script for me to send manually via my LinkedIn
• Compliant with GDPR and Privacy regulations across the US, UK and Europe
• Compliant with LinkedIn and job board terms and conditions
• Cost effective in terms of data processing, storage and CPU, balanced against performance
Technology choices are up to you, but I expect modern NLP / LLM tooling (Python, LangChain, OpenAI, Claude Code or similar) and clear, well-commented code so the pipeline can be expanded later.
Deliverables
– Working script or micro-service that runs locally (CLI or simple web UI is fine).
– A sample JSON or CSV output for at least three dummy candidates.
– Brief README explaining setup, environment variables (API keys), and how to retrain or fine-tune extraction rules if needed.
Acceptance criteria
1. All three data sources are successfully parsed and merged.
2. Skills, work experience and preferences are correctly extracted and appear in the output.
3. Vacancy shortlist clearly orders roles by relevance with a short rationale.
4. Setup from clean machine to first run takes under 15 minutes following the README.
If you already have experience with résumé parsing, web scraping, LinkedIn or Metaview integrations, that will jump you to the front of the line. I’m ready to start as soon as I find the right partner.
No vibe coders without prior software development and architecture experience please.
Here is what I need the agent to handle end-to-end:
• Ingest the three data sources (CV, LinkedIn profile, Metaview interview notes) and keep them linked to the same candidate record.
• Extract and normalise skills & competencies, work experience, plus any stated or implied preferences for the ideal next role. The skills and experience must be pulled from every data source, not just one.
• Use the consolidated profile to query company career pages, job boards or an internal vacancy API, rank matches by fit, and output a concise shortlist with an explanation of why each role is a match.
• Exclude vacancies from recruitment agencies, executive search and headhunting companies
• identify vacancy contact / hiring manager where possible
• Automate production of MVP email to the vacancy contact / hiring manager, with anonymised details of candidates. Where unable to automate the send, automate the script for me to send manually via my LinkedIn
• Compliant with GDPR and Privacy regulations across the US, UK and Europe
• Compliant with LinkedIn and job board terms and conditions
• Cost effective in terms of data processing, storage and CPU, balanced against performance
Technology choices are up to you, but I expect modern NLP / LLM tooling (Python, LangChain, OpenAI, Claude Code or similar) and clear, well-commented code so the pipeline can be expanded later.
Deliverables
– Working script or micro-service that runs locally (CLI or simple web UI is fine).
– A sample JSON or CSV output for at least three dummy candidates.
– Brief README explaining setup, environment variables (API keys), and how to retrain or fine-tune extraction rules if needed.
Acceptance criteria
1. All three data sources are successfully parsed and merged.
2. Skills, work experience and preferences are correctly extracted and appear in the output.
3. Vacancy shortlist clearly orders roles by relevance with a short rationale.
4. Setup from clean machine to first run takes under 15 minutes following the README.
If you already have experience with résumé parsing, web scraping, LinkedIn or Metaview integrations, that will jump you to the front of the line. I’m ready to start as soon as I find the right partner.
No vibe coders without prior software development and architecture experience please.